El Proceso de precarización en el mercado de trabajo del Gran La Plata. Principales características y tendencias actuales (2003-2004)

El objetivo del presente artículo es identificar las principales características y tendencias del trabajo precario en el Gran La Plata considerando la dinámica económica nacional actual. Tomando como parámetro el empleo pleno, pueden identificarse distintos grados de precariedad según la carencia de los atributos que caracterizan dicha plenitud. Existiría así una gradación de situaciones, con una referencia máxima en el empleo pleno hasta una mínima en el desempleo absoluto. El análisis partió de procesamientos propios de datos brindados por la Encuesta Permanente de Hogares (EPH). Abarca el período comprendido entre el segundo semestre de 2003 y el primero del 2004, debido a que tras la reformulación EPH sólo se dispone a la fecha de información específica de ese período. Los resultados del trabajo realizado dan cuenta de que, en la región, los trabajadores precarios representan el 39,3 de la PEA en el primer semestre de 2004. Si se suma el sector de los desocupados, la Población con Problemas de Empleo supera el 50 y muestra la presión que ejercen sobre el mercado laboral los subocupados demandantes. En el sector estatal, el 16,4 de los empleados están precarizados. Si se suman los beneficiarios de planes de empleo la cifra se eleva al 34. En el sector privado, el empleo precario comprende al 54 de sus trabajadores. Respecto a la evolución de los ingresos aun en los grupos de ocupados que mejoraron su capacidad de consumo entre 2003 y 2004, los niveles de ingresos alcanzados se hallan muy por debajo de los que percibían antes de la devaluación de 2002. Los principales aportes del trabajo consisten en la identificación, cuantificación y caracterización del empleo precario en la región en la etapa post-devaluación, sobre el análisis de la Base Usuaria de la EPH.

El Proceso de precarización en el mercado de trabajo del Gran La Plata. Principales características y tendencias actuales (2003-2004)

El objetivo del presente artículo es identificar las principales características y tendencias del trabajo precario en el Gran La Plata considerando la dinámica económica nacional actual. Tomando como parámetro el empleo pleno, pueden identificarse distintos grados de precariedad según la carencia de los atributos que caracterizan dicha plenitud. Existiría así una gradación de situaciones, con una referencia máxima en el empleo pleno hasta una mínima en el desempleo absoluto. El análisis partió de procesamientos propios de datos brindados por la Encuesta Permanente de Hogares (EPH). Abarca el período comprendido entre el segundo semestre de 2003 y el primero del 2004, debido a que tras la reformulación EPH sólo se dispone a la fecha de información específica de ese período. Los resultados del trabajo realizado dan cuenta de que, en la región, los trabajadores precarios representan el 39,3 de la PEA en el primer semestre de 2004. Si se suma el sector de los desocupados, la Población con Problemas de Empleo supera el 50 y muestra la presión que ejercen sobre el mercado laboral los subocupados demandantes. En el sector estatal, el 16,4 de los empleados están precarizados. Si se suman los beneficiarios de planes de empleo la cifra se eleva al 34. En el sector privado, el empleo precario comprende al 54 de sus trabajadores. Respecto a la evolución de los ingresos aun en los grupos de ocupados que mejoraron su capacidad de consumo entre 2003 y 2004, los niveles de ingresos alcanzados se hallan muy por debajo de los que percibían antes de la devaluación de 2002. Los principales aportes del trabajo consisten en la identificación, cuantificación y caracterización del empleo precario en la región en la etapa post-devaluación, sobre el análisis de la Base Usuaria de la EPH.

Aboveground community and species-specific plant biomass from the Jena Experiment (Main Experiment, year 2003)

This data set contains aboveground community biomass (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in 2003 just prior to mowing (during peak standing biomass in late May and in late August) on all experimental plots of the main experiment. This was done by clipping the vegetation at 3 cm above ground in four rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. the central 10 x 15 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for the biomass measures on the community level are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship.

Aboveground community and species-specific plant biomass from the Jena Experiment (Dominance Experiment, year 2003)

This data set contains aboveground community plant biomass (Sown plant community, Weed plant community, and Dead plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the dominance experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the dominance experiment, 206 grassland plots of 3.5 x 3.5 m were established from a pool of 9 plant species that can be dominant in semi-natural grassland communities of the study region. In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 3, 4, 6, and 9 species). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in May and August 2003 on all experimental plots of the dominance experiment. This was done by clipping the vegetation at 3 cm above ground in two rectangles of 0.2 x 0.5 m per experimental plot. The location of these rectangles was assigned by random selection of coordinates within the central area of the plots (excluding an outer edge of 50cm). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material, and remaining plant material that could not be assigned to any category. All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The mean of both samples per plot and the individual measurements are provided in the data file. Overall, analyses of the community biomass data have identified species richness and the presence of particular species as an important driver of a positive biodiversity-productivity relationship.

Abundance of zooplankton based on a long-term study at the Galata transect and covers the spring-summer periods from 1967 till 2005

The dataset is based on a long-term study (38 years) at the Galata transect and covers the spring-summer periods from 1967 till 2005. The whole dataset is composed of 360 data of total zooplankton biomass and abundance . Samples were collected in discrete layers 0-10m, 10-20m, 10-25m, 25-50m, 50-70m, 50-100m, 100-150. Mesozooplankton abundance: the collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Fishery Resource by Prof. Asen Konsulov and Institute of Oceanology by Prof. Asen Konsulov, Lyudmila Kamburska and Kremena Stefanova using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). Taxon-specific mesozooplankton abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber for taxomomic identification and count. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Fishery Resource by prof. Asen Konsulov and Institute of Oceanology by Prof. Asen Konsulov, Lyudmila Kamburska and Kremena Stefanova using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972).

Water chemistry of lakes in Zackenbergdalen between 1997-2003, East Greenland

The ecology of arctic lakes is strongly influenced by climate-generated variations in snow coverage and by the duration of the ice-free period, which, in turn, affect the physical and chemical conditions of the lakes (Wrona et al., 2005, http://www.acia.uaf.edu/PDFs/ACIA_Science_Chapters_Final/ACIA_Ch08_Final.pdf). Most arctic lakes are characterised by a long period (8-10 months) of ice-cover, cold water and low algal biomass. The water temperature and nutrient concentrations, and most probably the nutrient input from the catchments, are closely related to the duration of snow- and ice-cover in the lakes. In years when the ice-out is late, - that is, in late July, - phytoplankton photosynthesis is limited by the lack of light and nutrients. Less food is then available to the next link in the food chain, such as copepods and daphnids, with implication on their growth rates.